Bacteroides thetaiotaomicron and the specialist Akkermansia muciniphila in vitro and in vivo. The in vitro study, in which mucin was the only nutrient source, indicated that B. thetaiotaomicron significantly upregulated genes coding for Glycoside Hydrolases (GHs) and mucin degradation activity when cultured in the presence of A. muciniphila. Furthermore, B. thetaiotaomicron significantly upregulated the expression of a gene encoding for membrane attack complex/perforin (MACPF) domain in co-culture. The transcriptome analysis also indicated that A. muciniphila was less affected by the environmental changes and was able to sustain its abundance in the presence of B. thetaiotaomicron while increasing the expression of LPS core biosynthesis activity encoding genes  as well as ABC transporters. Using germ-free mice colonized with B. thetaiotaomicron and/or A. muciniphila, we observed a more general glycan degrading profile in B. thetaiotaomicron while the expression profile of A. muciniphila was not significantly affected when colonizing together, indicating that two different nutritional niches were established in mice gut. Thus, our results indicate that a mucin degrading generalist adapts to its changing environment, depending on available carbohydrates while a mucin degrading specialist adapts by coping with competing microorganism through upregulation of defense related genes.The human gastrointestinal tract is colonized by a diverse microbial community, which plays a crucial role in human health. In the gut, a protective mucus layer that consists of glycan structures separates the bacteria from the host epithelial cells. These host-derived glycans are utilized by bacteria that have adapted to this specific compound in the gastrointestinal tract. Our study investigated the close interaction between two distinct gut microbiota members known to use mucus glycans, the generalist  N-acetylgalactosamine , N-acetylglucosamine (GlcNAc), fucose (fuc), galactose , and sialic acid (Neu5ac)    mucin degrading enzymes to utilize mucus glycans as the sole carbon, energy and nitrogen source  and a glycan generalist (B. thetaiotaomicron). Mono-associated bioreactors were inoculated and used as control. Host-microbe interactions were evaluated through a gnotobiotic mouse model colonized with the same set of microbes.To investigate the microbe-to-microbe interaction under the continuous influx of host-derived glycans (mucin), we developed an A. muciniphila ATCC BAA-835 and B. thetaiotaomicron VPI-5482 in bioreactors with a continuous feed of mucin glycans. The bioreactors were sampled for measurements of metabolite production and total mRNA at the end of fermentation (120 h). The co-culture was characterized by higher growth and metabolic profile compared to the mono-associated bioreactors  of acetate and propionate compared to their monocultures. Moreover, as expected, 1,2-propanediol and succinate were also observed during the fermentation period, indicating continued fermentation of the monosaccharides released from the mucus glycans degradation. The amounts of SCFAs in the different conditions are shown in We established monocultures and a co-culture of reactors . The totectively . A. muciA. muciniphila and B. thetaiotaomicron to use their glycan degradation machinery. We measured expression of the genes from B. thetaiotaomicron and A. muciniphila in the community involved in carbohydrate metabolism and glycan biosynthesis and metabolism. The transcriptome data indicated that 306 genes from B. thetaiotaomicron involved in carbohydrate metabolism and glycan biosynthesis and metabolism were significantly different in the mono- and co-culture conditions. A total of 4% of these genes were significantly upregulated in the co-culture (q < 0.05). B. thetaiotaomicron expressed 218 of the 220-known mucin-degrading genes in both conditions. In the co-culture, B. thetaiotaomicron overexpressed (above 7.0-fold change) two genes coding for d-glycero-d-manno-heptose 1-phosphate kinase (BT_0474) and phosphoheptose isomerase (BT_0475) activity, respectively. Both genes were predicted to be involved in lipopolysaccharide biosynthesis. The capacity of B. thetaiotaomicron to utilize different complex dietary oligosaccharides relies on 88 polysaccharide utilization loci (PULs), which encompasses 18% of its genome  and BT_3324-49 (chondroitin sulfate) were significantly expressed in the monoculture  and lipid-A biosynthesis acyltransferase protein (Amuc_1541) . From the 53 mucin-degrading genes found in our A. muciniphila transcriptome data, seven were significantly upregulated in the co-culture (>2.0 fold-change)  .B. thetaiotaomicron altered its hydrolytic machinery between the two conditions. A significant increase in gene expression was detected for β-glucosidases , α-glucosidase (GH31), β-galactosidases , α-galactosidase , α-L-arabinosidase (GH43), α-L-fucosidases , α-mannanases (GH76), and α-L-rhamnosidases (GH78) in the co-culture  from different families , with GT2 (8 genes) and GT4 (3 genes) being the most representative GT families in the co-culture  in the co-culture compared to monoculture were analyzed in detail. -culture . We also-culture . Also, p-culture . InteresA. muciniphila showed a significant increase of three GH families that are predicted to be involved in the glycan degradation pathway. Namely, β-galactosidases (GH2), β-N-acetylhexosaminidases (GH20), and α-L-fucosidases (GH29) were significantly enriched in the co-culture. Furthermore, two families of GTs (GT2 and GT4) showed the highest increase of their overall expression in the co-culture conditions. Specifically, A. muciniphila significantly upregulated four genes encoding GT2 (Amuc_2094) and GT4   were upregulated in the co-culture and 415 genes (41%) were downregulated (B. thetaiotaomicron significantly upregulated two different operons (BT_2217–2221 and BT_3439–3441) of hypothetical proteins that exhibit the highest fold change compared to the monoculture. BT_2217-2221 exhibited between 30 and 120-fold change (q < 0.05). The other operon (BT_3439–3441) exhibited between 60 and 96-fold change (q < 0.05). The latter cluster contains a BT_3439 gene that encodes for the Membrane Attack Complex/Perforin (MACPF) domain-containing protein. Furthermore, the metabolism of terpenoids and polyketides  and the signal transduction  were the most variable metabolic processes in the co-culture  were upregulated and the rest 107 genes (24%) were downregulated in the co-culture  of a gene cluster that consists of two ABC transporter permeases (Amuc_1304 and Amuc_1305), two phosphate-binding proteins (Amuc_1304 and Amuc_1306) and is found to be part of the same gene operon (Amuc_1295–1306). In addition, three genes that belong to the same operon and encode for transporter permease (Amuc_1379 and Amuc_1380) and ATP-binding protein (Amuc_1381) activity, exhibited more than a 2.0-fold difference in the co-culture. Additionally, three membrane transport genes from the same operon (Amuc_0143-45) were predicted to be involved in the oligopeptide transport system. These genes that encode for oligopeptide substrate-binding (Amuc_0145) and permease  protein activity exhibited above a 1.5-fold difference in the co-culture conditions (q < 0.05). Furthermore, the transcriptome analysis revealed a significant upregulation  of genes that were involved in a two-component system pathway . The 50 most variable and the most significantly upregulated genes from both members of the community are illustrated in -culture . InteresB. thetaiotaomicron in the in vivo conditions showed no significant differences in the regulation of host glycan-degrading genes or the PULs between mono-colonization and co-colonization.Thereafter, we investigated the mono- and co-culture conditions in a gnotobiotic mouse model. Samples from the cecum and distal colon were taken for the quantification of the bacterial counts as well as the total RNA extraction and transcriptome data were generated. The transcriptome analysis of B. thetaiotaomicron was found to be more abundant than A. muciniphila in both cecum (1.10 × 105 ± 3.74 × 104 cells/ng of DNA) and distal colon (1.24 × 105 ± 6.30 × 103 cells/ng of DNA) in the co-culture  of the genes involved in two-component system pathways (Amuc_0827 and Amuc_0831 and Amuc_1151–1152) for A. muciniphila. Furthermore, 17 genes within the operon Amuc_2077–Amuc_2097  were differentially expressed, which demonstrated more than a 1.6-fold change in the co-colonized mice. Interestingly, nine genes of this operon (45%) were found to encode for glycosyl transferase activity (GT2 and GT4). On the other hand, fourteen genes involved in carbohydrate metabolism and four genes participating in glycan biosynthesis and metabolism were found to be significantly downregulated in the co-colonized mice.During the 14 days of colonization period, the mice received a standard diet rich in dietary fibers (chow diet). In the end of the colonization period, we showed that both bacteria colonized both cecum and distal colon of mice. -culture . The trazed mice , while nB. thetaiotaomicron and A. muciniphila was monitored by total RNA-sequencing of the cecum and distal colon. The transcriptional profile showed no significant differences in mouse cecum response between mono-colonization with B. thetaiotaomicron and co-colonization. In the distal colon, the comparison of B. thetaiotaomicron mono-associated mice with the co-associated revealed 228 significantly upregulated genes in the co-colonized mice. The 10 most significantly impacted genes in the co-colonized mice  exhibited more than a 2.0-fold difference. Next, six genes showed more than a 10-fold difference in the co-associated mice  (Host response toward the colonization with mono- and co-cultures of  Casp14) . FinallyA. muciniphila associated mice  encoding gene was significantly overexpressed in the co-associated mice . Additionally, genes encoding for protein glycosylation activity were upregulated non-significantly in the co-colonized mice. No significant differences were noticed in the expression of cecal mucin genes in the mice colonized with the two bacteria. In the distal colon, no significant differences in the mice's responses between mono-colonization with A. muciniphila and co-colonization were found. In the distal colon, though, a higher expression of mucin genes  was detected in the co-colonization study compared to mono-colonization.The transcriptional profile showed 23 genes significantly affected by the presence of glycan degraders together in mouse cecum compared to ted mice . The 10 A. muciniphila and a mucin-degrading generalist B. thetaiotaomicron during growth in vitro and in vivo conditions. The results demonstrated that these two glycan-degrading bacteria reached a stable state over time in vitro where both species co-exist and are metabolically active. Furthermore, the transcriptional response of both bacteria was altered when they were cultured together in either a lab bioreactor or animal gut.This study investigated the interaction between a mucus-degrading specialist, in vitro co-culture, B. thetaiotaomicron showed increased expression of its hydrolytic machinery. A possible explanation for this might be that B. thetaiotaomicron in the presence of A. muciniphila attempts to reach the mucin glycans by deploying as many GHs as possible to gain a competitive advantage. Another possible explanation is that B. thetaiotaomicron attempts to reduce A. muciniphila's fitness in the community. The latter is often described as an exploitative competition where a member of the community restricts the competitor's access to nutrients via the secretion of digestive enzymes , β-hexosaminidase (GH20), and α-L-fucosidase (GH29), targeting O-glycans linkages also found in mucin. However, A. muciniphila displayed no alterations in its glycan degrading machinery between mono or co-culture conditions, which demonstrates the robustness of the bacterium in a community where the only source of nutrients is mucin glycans. Exploitative competition for nutrients was also observed during the in vivo experiment. We observed an overall increase in GHs expression in co-culture conditions from both A. muciniphila and B. thetaiotaomicron. Since there is no evidence that A. muciniphila can utilize dietary fibers, we suggest that two different niches for bacterial colonization were established during the mice colonization.In the in vitro co-culture, B. thetaiotaomicron significantly upregulated a cluster of genes encoding hypothetical proteins (BT_2217 – 2221). Three genes of this cluster  were earlier characterized as C10 protease genes that encode for the C10 family of papain-like cysteine proteases, three of which are genetically clustered, and are associated with two staphostatin-like inhibitors  that may play diverse roles in the interaction with the host  from B. thetaiotaomicron, which encodes a gene for membrane attack complex perforin (MACPF) activity (BT_3439)  in the co-culture than in the monoculture. B. thetaiotaomicron is known to secrete antimicrobial proteins known as Bacteroidales-secreted antimicrobial proteins (BSAPs)  of the sensitive Bacteroidetes strains that lack the MACPF protein. To date, no study has described the activity of BSAPs against other members of microbial communities, except for Bacteroidetes-sensitive strains. However, in our study, the high fold-change of B. thetaiotaomicron MACPF expression in the co-culture may imply that B. thetaiotaomicron uses the MACPF to obtain survival advantage in the community. Additionally, for given Bacteroides species the MACPF genes are adjacent to the LPS core biosynthesis operon encoding also the replacement glycosyltransferase (GTs) genes of the target strains . On the other hand, one would expect that A. muciniphila abundance in the co-culture would be affected by B. thetaiotaomicron's attempt to reduce its fitness, but this is not what we observed. In co-culture conditions, both in vitro and in vivo, A. muciniphila significantly upregulated ABC transporters. It has been described before that ABC transporters involved in membrane transport provide antimicrobial peptide resistance  and the cecum , a gene encoding for O-antigen ligase activity (Amuc_0088). This A. muciniphila O-antigen was found to be a neighboring gene of the capsular polysaccharide biosynthesis protein (Amuc_2078)  were above a 2.5-fold change in the co-culture in vitro, while, in the cecum, all nine GTs  of this cluster exhibited more than a 1.5-fold difference in the co-culture. Therefore, A. muciniphila in a highly competitive environment may be resistant to antimicrobial peptides by using its putative LPS-associated core biosynthesis genes.B. thetaiotaomicron in mice's distal colon and A. muciniphila mice's cecum altered the host's response compared to the co-culture. In distal colon co-culture, the host significantly upregulated genes encoding for glycosyltransferase  and sulfotransferase activity (Chst3) involved in protein glycosylation. A recent study observed that more glycosyltransferases, involved in Muc2 O-glycosylation, were detected in the colon than in the small intestine  synthesize lactosamine elongations  and its abundance in a competitive environment implies a colonization advantage of A. muciniphila in the gut. Overall, this study gives more insight in how gut microbes adapt to their environment and respond toward host conditions and other microbiota members.This study demonstrated that two-glycan degrading bacterial species respond to a nutrient deficit by expressing genes encoding for protein activity related to glycan-degrading enzymes as well as ABC transporters and antimicrobial proteins as a result of their interaction. We showed that when mucin glycans were the only source of nutrients in the environment, Akkermansia muciniphila MucT (ATTC BAA-835) and Bacteroides thetaiotaomicron (VPI-5482) were grown in basal medium as described previously  filled with 250 ml of basal medium as it has been described before . Experiments were performed with 1% (v/v) supplementation of CaCl2 and vitamin mixture as described previously. The media in both feed and bioreactors were reduced with 0.05% l-Cysteine-HCl in order to achieve anaerobic conditions. The bioreactors were inoculated with a normalized O.D. of 1.0 of both species to achieve same starting cells density in the beginning of the fermentation. The flow rate of the feed was set at 20 ml/h and the recovery rate of media was 12.5 h. In the end of the fermentation (120 h) samples were taken for total RNA extraction. The growth was measured by spectrophotometer as optical density at 600 nm. The experiment was done in three biological replicates. Plugge,  at 37°C,Mus musculus), were used in the current study. All mice were obtained from the in-house breeding facility. The GF status of the mice was tested by culturing fecal bacteria anaerobically and aerobically, and also by PCR for bacteria 16S rDNA using the primers 27F and 1492R. One week prior the experiment mice were moved from the breeding isolators to the dedicated experimental isolators. For all colonization experiments, mice were maintained the plastic experimental isolators, in open top cages with dimensions 20 × 14 × 35 cm  with wooden bedding , housed in a climate-controlled room (20 ± 2°C and 60% humidity) and subjected to a strict 12 h light/dark cycle (7:00 a.m. −7:00 p.m.) with free access to autoclaved water and food. Mice were fasted at 9:00 a.m. for 4 h prior gavage  with 0.2 ml of active culture (for both mono- and co-colonization). We have estimated the group size based on previously published studies where GF mice were colonized either with Akkermansia muciniphila or Bacteroides thetaiotaomicron  and bi-colonization (n = 7 mice) 108 CFU/ml bacterial culture have been used. For A. muciniphila (n = 8 mice) mono-colonization 109 CFU/ml bacterial culture have been used. For all three colonization, mice were inoculated with a single gavage of the respective culture. The mice received during the 14 day of colonization chow diet . At the end of the study mice were euthanized by cervical dislocation. Intestinal segments  were harvested and immediately snap-frozen in liquid nitrogen and stored at −80°C until further processed. Cecum and distal colon content were collected and stored in RNA Later (Sigma) at −20°C until further processed.The study was conducted in accordance with institutional guidelines for the care and use of laboratory animals. All animal procedures related to the purpose of the research were approved by the University of Gothenburg Animal Studies Committee under the Ethical license of the national competent authority, securing full compliance the European Directive 2010/63/EU for the use of animals for scientific purposes. Female, 10–12 weeks old Swiss Webster germ free (GF) mice . RNA concentration was measured by nanodrop and RNA quality was assessed by Qsep bioanalyzer .Total RNA was isolated for both the bioreactors' samples and mice intestinal segments  by a method combining the Trizol® reagent and the RNeasy Mini kit  as described previously  using the following parameters k = 31 and ref=riboKmers.fa.gz. Transcripts from the reference strain of A. muciniphila (GCF_000020225.1) have been quantified with RSEM (v1.3.1)  < 0.05 and Log2 Fold Change >0.58 were considered significant. The datasets presented in this study are deposited in the European Nucleotide Archive (https://www.ebi.ac.uk/ena), under accession PRJEB41424.Illumina reads have been trimmed for low quality and adapters with fastp (v0.20.0) (21) using default settings. rRNA sequences have been removed with bbduk (v38.79) . The genomic DNA from the in vivo samples  content was isolated using bead beating. The steps that were followed during DNA isolation from cecum and distal colon are listed in A. muciniphila  were used for quantification. Standard curves of both species were prepared with nine standard concentrations from to 100 to 108 gene copies/μl. qPCR was performed in triplicate with iQ SYBR green supermix (Bio-Rad) in a total volume of 13 μl prepared with primers at 500 nM in 384-wells plates with the wells-sealed with optical sealing tape. Amplification was performed with an iCycler (Bio-rad) and the following protocol: one cycle of 95°C for 10 min; 40 cycles of 95°C for 15 s, 60°C for 20s, and 72°C for 30 s each; one cycle of 95°C for 1 min; and a stepwise increase of temperature from 60 to 95°C (at 0.5°C per 5 s) to obtain melt curve data. Data were analyzed using the Bio-Rad CFX Manager 3.0.The abundance of 2SO4 as eluent. All samples and standards (10 μl injection volume) ran for 20 min. Standards were prepared with concentrations ranging from 2.5 to 25 mM.For fermentation product analysis, samples were obtained at different time points of the incubation period. Crotonate was used as the internal standard and the external standards were lactate, formate, acetate, propionate, butyrate, isobutyrate, 1,2-propanediol, sialic acid, and glucose. Substrate conversion and product formation were measured with Shimadzu LC_2030C equipped with a refractive index detector and a Shodex SH1011 column. The oven temperature was set at 45°C with a pump flow of 1.00 mL/min using 0.01N Ht-test was used and corrected for multiple testing using False Discovery Rate (FDR) correction for multiple corrections. Data are presented as mean ± standard deviation (SD), unless stated otherwise. Adjusted p < 0.05 were considered significant.Statistics were performed using student's https://www.ebi.ac.uk/ena, PRJEB41424.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: The animal study was reviewed and approved by University of Gothenburg Animal Studies Committee.in vitro experiments and obtained and analyzed all the data with the assistance of SA. PK-D performed the in vivo experiment. BN processed the raw RNA-sequencing data through an internal pipeline and deposited and made the data publicly open in an acceptable repository. SA and CB were also involved in the interpretation of the results and wrote the manuscript. FB, JK, and WV supervised the work. CB conceived and supervised this work. All authors have read the manuscript and approved it for submission.IK and CB designed the experiments. IK performed the JK is on the payroll of Nutricia research. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Paenarthrobacter sp. AT-5, an atrazine-degrading strain, was inoculated into agricultural soils contaminated with atrazine to investigate the bioaugmentation process and the reassembly of the soil microbiome. It was found that 95.9% of 5 mg kg−1 atrazine was removed from the soils when inoculated with strain AT-5 with 7 days, and the phytotoxicity of sweet potato caused by atrazine was significantly alleviated. qRT-PCR analysis revealed that the inoculated strain AT-5 survived well in the soils and maintained a relatively high abundance. The inoculation of strain AT-5 significantly affected the community structure of the soil microbiome, and the abundances of bacteria associated with atrazine degradation were improved.Atrazine, a triazine herbicide, is widely used around the world. The residue of atrazine due to its application in the fore-rotating crop maize has caused phytotoxicity to the following crop sweet potato in China. Bioaugmentation of atrazine-contaminated soil with atrazine-degrading strains is considered as the most potential method to remove atrazine from soil. Nevertheless, the feasibility of bioaugmentation and its effect on soil microbiome still need investigation. In this study,  Atrazine is widely used in the prevention and control of broad-leaved weeds in maize, pineapple, sorghum, and sugar cane . Since a in soil , 30 μgL−undwater , and 5 μce water . As a poce water , nervousce water , and repce water . Furtherce water , sorghumce water . TherefoPseudomonas sp. strain ADP, which is the first isolated atrazine-mineralizing strain  to evaluate the stability and fate of strain AT-5 during the bioaugmentation process. At the same time, the alleviation of phytotoxicity of sweet potato by strain AT-5 was also investigated. More importantly, our study also aims to explore the dynamic changing process of soil microbiome during bioaugmentation. This study is helpful to understand the change of community structure of microbiome during bioaugmentation and provides a theoretical guidance for development of enhanced bioremediation strategies for atrazine-contaminated soils.In this study, an atrazine-degrading strain, Soil samples were collected from a maize field (0–10 cm depth) in Jiangsu Province, China, after maize was harvested. Mixed and homogenized soil samples were passed through a 2-mm sieve and then stored at 4°C before further use. The chemical and physical properties of the soil were determined by standard methods  and summPaenarthrobacter sp. strain AT-5, an atrazine-degrading strain isolated previously in our lab (g for 6 min) and washed with sterilized minimal salt medium for three times. our lab , was use−1, 5 mg kg−1, 1 mg kg−1, 0.5 mg kg−1, and 0.2 mg kg−1, dry soil weight). The atrazine-spiked soils  were transferred to three pots, respectively. The “Su 22” sweet potato seedlings were planted into pots and put in a growth chamber  at 28/25°C with an 18-h light/6-h dark cycle. During the incubation, water was added every other day to keep the soil moisture content at 40%. The growth status of sweet potato seedlings was observed and recorded at 0, 1, 3, 7, 14, and 21 days, and three replicates were set for each treatment.To study the phytotoxicity of subsequent crop caused by atrazine residues in soil, the “Su 22” sweet potato seedlings  were selected. Soils with atrazine residues were prepared by supplementing atrazine  to soils at five different final concentrations (10 mg kg−1 (dry soil weight), and the carrier solvent methanol was removed through evaporation. The microcosm treatments were set as follows: (i) Control: equivalent amount of methanol and ddH2O were added into native soil, (ii) Atr: native soil spiked with atrazine, (iii) Atr-Bio: atrazine-spiked soil with inoculation of strain AT-5 (1.0 × 107CFU/g dry soil), (iv) Bio: native soil with inoculation of strain AT-5 (1.0 × 107CFU/g dry soil), and (v) Sterilized soil: atrazine-spiked soil autoclaved three times . The treated soils were sorted into plastic pots (700 g dry soil per pot) and then incubated at 28/25°C with an 18-h light/6-h dark cycle in a growth chamber for 14 days. The soil moisture content was kept at 30% of the soil water holding capacity (WHC), and the lost water was replenished by weighing samples every day. Soils (20 g per pot) were non-destructively sampled at 0, 1, 3, 5, 7, and 14 days for atrazine detection and bacterial community analysis. Three replicates were set for each treatment.Atrazine-spiked soils were prepared as described above at a final atrazine concentration of 5 mg kgThe remaining soils of the atrazine-spiked soil (Atr) and atrazine-spiked soil with inoculation of strain AT-5 (Atr-Bio) at 14 d were planted with sweet potato seedlings to verify whether the phytotoxicity caused by atrazine was alleviated by bioaugmentation with strain AT-5. The growth status of sweet potato seedlings was measured as described in section “Phytotoxicity of Sweet Potato Caused by Atrazine and Its Alleviation by Bioaugmentation”.18 separation column . The mobile phase consisted of 20% water and 80% methanol (vol/vol), and the flow rate was 0.8 ml min−1. The column temperature was 30°C, and the injection volume was 20 μl. Atrazine was detected at 220 nm. Under these conditions, the retention time (Rt) for atrazine was 5.97 min.At each sampling time, 20 g soil (dry weight) was collected and extracted three times with 60 ml dichloromethane by horizontally mixing for 2 h at 30°C and ultra-sonication for 30 min. The extracts were concentrated by rotary evaporation, dried with nitrogen, and then resolved in 1 ml of methanol. Using this method, the extraction efficiency of atrazine in soil was 79.9%. The impurities in the extracts were removed by filtering through a 0.22-μm membrane. Atrazine was detected through high-performance liquid chromatography  using a reversed-phase CSoil total DNA was extracted from the soil sample  using a Fast DNA SPIN Kit for Soil . The V4 region of the 16S rRNA gene was amplified using the primer set 515F and 806R as described previously . The amptrzN gene  through quantitative real-time PCR (qRT-PCR) with primers  and cloned into pMD™19-T Vectors . The recombinant plasmid was used as the standard for quantitative analysis. The concentrations of the recombinant plasmid were detected on a NanoDrop ND-2000 spectrophotometer , and then the copy numbers of inserted trzN gene were calculated. Tenfold serial dilutions of the concentration-known recombinant plasmid (in triplicate) were used in the qRT-PCR assay to generate an external standard curve. The qRT-PCR was performed on the Applied Biosystems 7500 Fast real-time PCR system  with SYBR Premix Ex Taq II .The numbers of the inoculated strain AT-5 in soil were estimated by quantifying the copy numbers of After sequencing, the raw reads were merged using FLASH . The merThe sequencing data involved in this manuscript are available at NCBI under BioProject ID PRJNA765205.50 and DT90 values of atrazine in Atr-Bio treatment were 1.2 and 3.9 days, respectively. These results showed that indigenous microorganisms contributed a little to atrazine removal and strain AT-5 dominated the atrazine removal in the soil (p < 0.01).In the sterilized soil, only 14.5% of atrazine disappeared at the end of incubation (14 days), showing that abiotic factors have limited contributions to atrazine dissipation . ComparetrzN by qRT-PCR (trzN gene decreased within the first 7 days and then kept relatively stable (the same order of magnitude at 106 copies g−1 dry soil) till 14 days, while the trzN gene could not be amplified with the DNA template extracted from the original soil without any treatments. These results indicated that the inoculated strain AT-5 could survive well in the soil for a period of time (14 days).The abundance of the inoculated strain AT-5 in the soil was calculated by quantifying the copy numbers of the initial hydrolase gene  qRT-PCR . The amp−1) in the soil, the sweet potato seedlings survived within the 21-day cultivation period, but phytotoxicity phenomena, such as leaf yellowing, were still observed. These results suggested that sweet potato seedlings were sensitive to atrazine, and even low concentrations of atrazine in the soil would affect the planting of subsequent crops. Therefore, the remaining soils of the atrazine-spiked soil (Atr) and atrazine-spiked soil with inoculation of strain AT-5 (Atr-Bio) at 14 d were again planted with sweet potato seedlings. The concentrations of atrazine remaining in Atr and Atr-Bio soils were 3.36 ± 0.62 and 0.09 ± 0.002 mg kg−1, respectively. The atrazine-spiked soil (Atr) caused serious phytotoxicity to sweet potato seedlings, and sweet potato seedlings died at 21 days. However, the sweet potato seedlings grew well in the atrazine-spiked soil with inoculation of strain AT-5  presented higher community richness (represented by higher Chao1 indices and observed OTU numbers) and diversity (indicated by Shannon and Simpson indices) than the Atr-Bio treatment (atrazine-spiked soil with inoculation of strain AT-5) and the Bio treatment  and hierarchical cluster analysis were used to investigate the influences of inoculation of strain AT-5 and atrazine application on soil bacterial communities. The soil samples were grouped into two distinct clusters based on different treatments and time: inoculation treatments (Atr-Bio and Bio) and non-inoculation treatments . These results combined with the qRT-PCR data showed that the inoculated Paenarthrobacter sp. strain AT-5 stably survived in the soil . Furthermore, the abundance of Bacillus was significantly increased in the inoculation treatment, indicating that inoculation of Paenarthrobacter sp. strain AT-5 enriched the genus Bacillus in the indigenous microbiome. Meanwhile, the relative abundances of 17 other potential biomarkers including Marmoricola, Nocardioides, Agromyces, and Solirubrobacter, decreased in inoculation treatment as compared to that in other treatments. These results indicated that inoculation treatment negatively selected these genera in the indigenous microbiome. It is worth noting that the positively selected biomarkers, including Marmoricola, Nocardioides, Agromyces, and Solirubrobacter, were only detected in the atrazine-spiked soil treatment (Atr) at 14 days. They increased markedly in Atr treatment at 14 days as compared to that in 1, 3, and 7 days. These four genera might be the positive biomarkers for atrazine degradation in non-inoculation treatments.To identify the biomarkers distinguishing different treatments, LEfSe analysis was used . There wThe co-occurrence patterns of bacterial communities in different treatments  were identified through constructing bacterial co-occurrence networks. The topological properties of the co-occurrence patterns varied significantly between the Atr-Bio and Atr networks . The AtrPaenarthrobacter sp. AT-5 was inoculated for atrazine removal to investigate the effects of bioaugmentation on the soil microbiome and the reconstructing process of microbial community.Microbial communities in natural environments usually do not have the capacity to degrade organic pollutants. Bioaugmentation, a strategy of inoculating specific functional microorganisms for degradation of pollutants, has been proposed as the most potential method to clean up pollutant-contaminated sites . Though Arthrobacter sp. strain HB-5 was significantly reduced to 6.3 days  and Atr treatment (atrazine application). These results indicated that the main driving factor for the change of bacterial community structure in the inoculation treatments is the addition of strain AT-5. It has been reported that the abundance of inoculum decreased after elimination of pollutants in soils , the National Natural Science Foundation of China (31870095 and 41977120), and the China Agriculture Research System of MOF and MARA.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Streptococcus mutans biofilm.The aim of this study was to demonstrate the mode of action of glass ionomers (G-Is) against cariogenic biofilms in the slow fluoride release phase by analyzing the reciprocal interaction between fluoride release from G-Is and acid production of S. mutans biofilms were formed on these discs. The interrelationship between the acid production of the biofilm and the fluoride release of the G-Is discs was investigated by analyzing both factors simultaneously during the biofilm formation period. The composition of the 51 h-old biofilms was then examined using microbiological, biochemical, and confocal laser scanning microscopic methods.G-Is discs in the slow fluoride release phase were prepared and 51 h-old Acid production by the cariogenic biofilm, particularly at < pH 5, promotes G-Is fluoride release. Conversely, G-Is fluoride release inhibits the acid production of the cariogenic biofilm. This reciprocal interaction results in the reduction of virulence such as extracellular polysaccharides formation and cariogenic biofilm bio-mass, which may reduce the potential of secondary caries development around G-Is.These results suggest that G-Is may play a role in preventing the development of secondary caries during the slow fluoride release phase. Streptococcus mutans, a primary cariogenic bacterium, can synthesize extracellular polysaccharides (EPSs) from sucrose. These EPSs contribute to the physical integrity and stability of biofilm matrixes, increasing biofilm virulence [Secondary caries is the most common cause of dental restoration replacement . Similarirulence . TherefoFluoride played a major role in the dramatic decline in dental caries from the 1950s to the 1980s as it promotes remineralization and slows down demineralization of dental tissue . FluoridIt is known that fluoride release in these materials occurs in a biphasic pattern . G-Is rePrevious studies have identified pH as the most important factor that influences G-Is fluoride release (a much greater amount of fluoride ions is released at acidic and cariogenic pH levels) . HoweverIn this study, we investigated the interaction between fluoride release from G-Is (during the slow release phase) and cariogenic biofilm acid production, and revealed the mode of action of the materials against cariogenic biofilms. The findings we report may offer a new perspective in the area of G-Is’ anti-caries activity.The materials used in this study are listed in the Supplementary Table. Four commercially available G-Is restorative materials were selected: GC Fuji Filling LC (GC), Ketac Fil Plus Aplicap (Ketac), Riva self-cure HV (Riva), and Unifil Flow (Unifil). These materials were used to prepare disc-shaped specimens (12 mm in diameter and 1.2 mm in thickness) according to previous studies . The G-IS. mutans UA159 (ATCC 700610) biofilms were formed on the prepared G-Is or HA discs and placed in a vertical position in 24-well plates [S. mutans UA159 (2–5 × 106 colony forming units (CFUs)/ml) and the biofilms were allowed to grow undisturbed for 22 h. From this time point (22 h) onward, the culture medium was changed twice daily  until it reached 51 h old.l plates . InitialThe experimental scheme for this study is detailed in Supplementary Figure S2. To investigate the mode of action of G-Is in the slow fluoride release phase against cariogenic biofilms, the following hypotheses were tested: 1) changes in the pH of the environment may affect the fluoride release of G-Is without cariogenic biofilms, 2) changes in the pH of the environment may affect the fluoride release of G-Is with cariogenic biofilms, 3) changes in fluoride release of G-Is may influence acid production of cariogenic biofilm, 4) in G-Is with cariogenic biofilm growth, fluoride release of G-Is and acid production of biofilm influence each other simultaneously. 5) as a result of this interrelationship between G-Is fluoride release and biofilm acid production, the final composition of cariogenic biofilms can be influenced. After testing the above hypotheses, the mode of action of G-Is against cariogenic biofilms during the slow fluoride release phase was outlined.2, pH = 3, 4, 5, or 7) [HA or G-Is discs in the slow fluoride release phase were transferred to a 12-well plate  containing a salt solution of varying pH  . These dS. mutans biofilms were formed on HA or G-Is discs in the slow fluoride release phase, the biofilms were transferred to a 12-well plate containing a salt solution of varying pH . These biofilms were allowed to incubate for 4 h at room temperature. At the 0.5, 1, 2, 3, and 4 h, the pH values and fluoride concentrations of the solution were determined.After 51 h-old S. mutans biofilms was determined using a glycolytic pH drop assay [−. The pH was adjusted to 7.0 using 0.2 M KOH before glucose  was added. The subsequent decrease in pH over 4 h was assessed using a glass electrode. We determined the test fluoride concentrations based on the range of G-Is fluoride release established in a previous study [The influence of fluoride on the acid production of op assay . The 51 us study .S. mutans biofilm formation on HA or G-Is discs were determined. These results were stratified by time or type of G-Is.To investigate the interrelationship between G-Is fluoride release and biofilm acid production, the pH values and fluoride concentrations of the old culture media replaced at 22, 31, 46, and 51 h during 51 h-old S. mutans biofilms on G-Is discs . Confocal laser scanning microscopic (CLSM) studies as described by Jeon et al. [3/μm2), thickness (μm), and coverage (%) of the bacteria and EPSs were quantified using the COMSTAT image-processing software [3) from a certain biofilm area divided by the surface area of the certain substratum (HA discs) (μm2). The coverage (%), which is the fraction of the area occupied by biomass in each image of a stack, reflects how efficiently each stack is colonized by bacteria or EPSs. The three-dimensional architecture of the biofilms was visualized using Imaris 8.0.2 .To determine whether the composition had changed, we used microbiological and biochemical methods to analyze the dry weight, CFUs and water-insoluble EPSs of 51 h-old n et al.  were alssoftware . The bio2), which describes the percentage of the variation in one variable that can be explained by the linear relationship with another variable, of each fitted line was also calculated. All experiments were performed in duplicate, and at least three different experiments were conducted. Data are presented as mean ± standard deviation. Intergroup differences were estimated using one-way analysis of variance, followed by a post hoc multiple comparison test (Tukey test). Values were considered statistically significant when the P value was < 0.05.To determine the relationship between pH and G-Is fluoride released, power, polynomial, and linear curve fitting were performed. The determination coefficient (R2 = 0.89–0.97) . After 89–0.97) -1, c-2).S. mutans biofilms were formed on the G-Is discs  . The flIs discs -1, b-2).ectively ). The fl89–0.97) ), simila89–0.97) .Figure − resulted in a higher solution pH by inhibiting acid production by S. mutans biofilms (2 = 0.99–1).In this study, fluoride in the range of 1–6 ppm Fbiofilms ). As shobiofilms , the fluS. mutans biofilm formation on G-Is discs can be considered the net result of the two-way relationship between G-Is fluoride release and biofilm acid production. As shown in 2 = 0.32–0.98), which suggested that the materials that released greater amounts of fluoride exhibited greater suppressions of acid production by S. mutans. For each G-Is over different time points, there was a correlation between the acidity and the amounts of the released fluoride in the spent media (2 = 0.61–0.99).The changes in fluoride release and pH levels during nt media -1-d-4). S. mutans biofilms changed. The dry weight and amount of water-insoluble EPSs of the G-Is biofilms were reduced, compared to those of the HA discs (P < 0.05) (P < 0.05) (P < 0.05)  . Convers < 0.05) ). Howeve < 0.05) ). The biin vitro experiment model to confirm the interaction between fluoride release of G-Is and acid production of cariogenic biofilm, and further demonstrated the prospective effect of this reciprocal relationship on cariogenic biofilm virulence and secondary caries development.Multiple studies have demonstrated the therapeutic effect of fluoride releasing G-Is, particularly with regard to their ability to enhance remineralization and inhibit demineralization of the dental hard tissues ,18. Surp2 = 0.89–0.97) for pH < 5 . These S. mutans is an important virulence in dental caries pathogenesis [S. mutans biofilms during biofilm formation  can influence S. mutans EPS formation [It has been well documented that EPS formation of ogenesis . In thisormation , Figure ormation -1, b-2).ormation -2). Thesr pH < 5 ). Howeveormation . Additioormation , suggestS. mutans biofilms on G-Is significantly greater than those of the HA disc biofilms . This ibiofilms , the bacAll in all, data in this study and from previous investigations suggest the following mode of action of G-Is in the slow fluoride release phase against cariogenic biofilms and subsequent secondary caries development : (1) A sIn the formation of cariogenic biofilms on/around G-Is, fluoride release from G-Is and acid production from cariogenic biofilms influence each other. Acid production by the cariogenic biofilm, particularly at < pH 5, promotes the release of G-Is fluoride. Conversely, the release of G-Is fluoride inhibits the acid production of the cariogenic biofilm. This two-way interaction results in the reduction of virulence, such as EPS formation and cariogenic biofilm bio-mass, which may reduce the potential of secondary caries development around G-Is. These results suggest that G-Is can play an important role in reducing the virulence of cariogenic biofilms and preventing subsequent formation of secondary caries if the fluoride release rate is adequate.Click here for additional data file.


Helicobacter pylori, herpes simplex virus 1, influenza virus subtype H1N1, influenza virus subtype H3N2, measles virus, Saccharomyces cerevisiae, Theiler’s virus, Toxoplasma gondii, and SAG1 protein domain, a surface antigen of Toxoplasma gondii measured for greater precision. We performed genome-wide association analyses of antibody levels against these 14 infections (N = 357 – 5010) and identified three genome-wide signals (P < 5×10-8), two associated with measles virus antibodies and one with Toxoplasma gondii antibodies. In an association analysis focused on the human leukocyte antigen (HLA) region of the genome, we further detected 15 HLA alleles at a two-digit resolution and 23 HLA alleles at a four-digit resolution associated with five antibodies, with eight HLA alleles associated with Epstein-Barr virus antibodies showing strong evidence of replication in UK Biobank. We discuss how our findings from antibody levels complement other studies using self-reported phenotypes in understanding the architecture of host genetics related to infections.The burden of infections on an individual and public health is profound. Many observational studies have shown a link between infections and the pathogenesis of disease; however a greater understanding of the role of host genetics is essential. Children from the longitudinal birth cohort, the Avon Longitudinal Study of Parents and Children, had 14 antibodies measured in plasma at age 7: Alpha-casein protein, beta-casein protein, cytomegalovirus, Epstein-Barr virus, feline herpes virus,  Helicobacter pylori has been linked to myocardial infarction  cohort by: (1) Investigating the options for analysing antibody titers to model antibody levels in terms of whether using measures as a continuous variable or thresholding to define infection status is most appropriate; (2) Identifying genome-wide single nucleotide polymorphisms (SNPs) strongly associated with the antibodies; (3) Identifying HLA alleles strongly associated with the antibodies; (4) Assessing consistency of genetic signals associated with the antibodies at different time points in ALSPAC and in an independent cohort (UK Biobank). (5) Evaluating whether any of the genetic signals identified overlap with SARS-CoV-2 infection (COVID-19 Host Genetics Initiative). This study extends the scope of understanding infection susceptibility and host genetics by increasing the range of infections examined and investigates infections in children.Pregnant women resident in Avon, UK with expected dates of delivery 1st April 1991 to 31st December 1992 were invited to take part in the ALSPAC study , 16. TheWhen the oldest children were approximately seven years of age, an attempt was made to bolster the initial sample with eligible cases who had failed to join the study originally. As a result, when considering variables collected from the age of seven onwards  there are data available for more than the 14,541 pregnancies mentioned above. The number of new pregnancies not in the initial sample (known as Phase I enrolment) that are currently represented on the built files and reflecting enrolment status at the age of 24 is 913 , resulting in an additional 913 children being enrolled. The phases of enrolment are described in more detail in the cohort profile paper and its update , 16. TheA 10% sample of the ALSPAC cohort, known as the Children in Focus (CiF) group, attended clinics at the University of Bristol at various time intervals between 4 to 61 months of age. The CiF group were chosen at random from the last 6 months of ALSPAC births (1432 families attended at least one clinic). Excluded were those mothers who had moved out of the area or were lost to follow-up, and those partaking in another study of infant development in Avon.http://www.bristol.ac.uk/alspac/researchers/our-data/). Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees. Consent for biological samples has been collected in accordance with the Human Tissue Act (2004).The study website contains details of all the data that is available through a fully searchable data dictionary and variable search tool  between September 1998 and October 2000 . AttendeSacchraromyces cerevisiae.Whole blood samples were collected and processed by centrifugation at 3500rpm, for 10 minutes at 4-5°C . SubsequAll target antigens and source of target antigens for each infection of interest have been detailed elsewhere . Serum aToxoplasma gondii (T. gondii), surface antigen 1 (SAG1) protein domain of T.gondii, cytomegalovirus (CMV), Epstein-Barr virus (EBV), herpes simplex virus type 1 (HSV1), influenza virus subtypes H1N1 and H3N2, measles virus, Saccharomyces cerevisiae (S. cerevisiae), Helicobacter pylori (H. pylori), feline herpes virus (FHV), Theiler’s virus (TV), bovine casein alpha protein  and beta protein (beta-casein).The antibodies examined in this analysis are against the following antigens: For each antibody, measurements of optical density were read directly from the ELISA plate. The ratio to standards were then derived from the standards measured on each plate. These ratios were then standardised to produce z-scores with a mean of two and a standard deviation of one per plate  . In addiNot all participants were measured for all 14 antibodies at every clinical time point. The antibody levels for each antigen at the seven-year time point were analysed in the primary analysis as they represented the largest sample size, and the distribution of z-scores for each infection did not largely differ across time points.-7. Cryptic relatedness was assessed as the proportion of identity by descent (IBD >0.1) described previously  subcontracting from the Wellcome Trust Sanger Institute, Cambridge, UK and the Laboratory Corporation of America, Burlington, NC, US. Genotypes were called with Illumina GenomeStudio and PLINK(v1.07)  was usedeviously .After quality control steps, a total of 9,115 individuals and 500,527 SNPs passed these filters. ALSPAC children were phased using ShapeIt v2  to phaseTwo software packages, HLA*IMP:03  and SNP2SNP2HLA_package_v1.0.3  was utilFor HLA*IMP:03 (v.0.1.0) , HLA impT, to determine concordance (-0.5 ≤ T ≤ 0.5) or discordance (-0.5 ≥ T ≥ 0.5) between the two approaches. The proportion of concordant and discordant HLA alleles at each given HLA loci were then tabulated. In addition, allele frequencies for each HLA loci were calculated for each HLA imputation approach, and values were compared to the T1DGC reference panel.Concordance of HLA imputation using the two packages were compared by assessing the difference in dosages by providing a call threshold, -6) from an analysis where the antibody measures were treated as a continuous variable. .It would be desirable to be able to stratify individuals into seropositive and seronegative for each antibody analysed. However, determining where to call the threshold for continuous antibody data is complex due to the unavailability of reliable assays on reliably determined controls to establish uninfected population baseline distributions ; (2) A swww.cog-genomics.org/plink/2.0/) (www.cog-genomics.org/plink/2.0/)  (nk/2.0/)  for eachnk/2.0/)  on all fwww.cog-genomics.org/plink/1.9/) (http://neurogenetics.qimrberghofer.edu.au/matSpDlite/)   and adjupDlite/)  was usedpDlite/)  was emplHelicobacter pylori, and Toxoplasma gondii. Analyses were performed using the initial assessment time point for all antigens . Antibody measurements were rank-based inverse normal transformed for all GWAS and HLA association analyses and beta estimates presented are on this scale. To give an idea of the magnitude of these effects, the main results are also presented using the z-scores of the ratio-to-standard measures, where beta estimates are a change in standard deviation per allele.Comprehensive description of UK Biobank’s cohort profile, serological measures and analyses performed are available in P-values were compared.To investigate genetic overlap, ALSPAC antibody association results and the SARS-CoV-2 GWAS meta-analysis findings (C2_ALL_eur) N = 1,683,784) Helicobacter pylori, Toxoplasma gondii, SAG1 protein domain), and eight had <700 individuals  (Distribution of the ratio to standards of the 14 antibodies are shown in evisiae) .We explored the utility of analysing the 14 antibodies as continuous or thresholded variables in ALSPAC children. Four threshold approaches (as described in the methods) were used: (1) Ratio to standards greater than or equal to 1; (2) A subjective threshold based visually identifying the trough in distributions that were clearly bimodal; (3) The threshold which demonstrated the most signal in a GWAS analysis; (4) The threshold that best recapitulated continuous GWAS results. These were also compared to proportions of seroprevalence measures reported in the literature  (versus 15-25%)  from the continuous GWASs across the thresholded GWASs for each specific antibody, to see if any thresholds gave similar association results on an individual locus basis. The thresholds which gave the most consistent results (to continuous) are shown in We compared the top SNP associations (P < 5 × 10-8) to two antibodies (Measles virus or T. gondii) and 26 suggestive SNPs (P < 1 × 10-6) associated with 12 antibodies. These SNPs are presented in T. gondii antibody, was retained after adjusting for the 14 antibodies tested (P < 3.6×10-9).We performed genome-wide association analyses of all continuous antibody measures at the seven-year clinic in ALSPAC and identified a total of three SNPs with strong associations , an intergenic SNP located between LOC105370271 and SCEL on chromosome 13q22.3. Followed by rs28617484 , also an intergenic SNP, between LINC01920 and LINC02612 on chromosome 2q23.3. In addition, stratified analysis by measles, mumps and rubella (MMR) vaccination status was performed on the genome-wide and suggestive SNPs. Findings in P > 0.001), with environmental exposure of the measles virus showing greater genetic signal (P > 2.6×10-6).The strongest association for measles virus was rs506576  located in GRAM Domain Containing 1B (GRAMD1B) on 11q24.1 . No evidence of an association was identified, with effect size shown in the opposite direction.For  11q24.1 –37. A loP < 4.3 ×10-4, adjusted for the three additional timepoints and the 29 associations tested), with all estimates showing consistency in the direction of effects  and antibodies against T.gondii, with effect sizes similar to that observed at the 7-year clinic (β = 0.20) also seen at the 11-year clinic  and the 15-year clinic , but this association was not seen at the earlier five-year clinic (P = 0.45).The strongest associations at different time points were demonstrated between rs36020612 (P = 7.1 × 10-7); rs117760947 . These effect sizes were similar to the effect sizes exhibited at the seven-year clinic: rs3104369 (β = -0.19); rs117760947 (β = 0.48), however these associations were not observed at the five-year and 15-year clinic (P < 0.83).For antibodies against feline herpes virus, two SNPs replicated at the 11-year clinic time point: rs3104369  and the eleven-year clinic , with comparable effect sizes shown at the two time points. These associations however were not able to be replicated at the five-year and 15-year clinic.Furthermore, rs35030589 was shown to be associated with antibodies against P = 5.6×10-5) and the 15-year clinic , although this association was not observed at the five-year clinic (P < 0.07).For antibodies against herpes simplex virus, rs10961934 showed the strongest associations at different timepoints. The effect size at the seven-year clinic (β = 0.53) were similarly demonstrated at the 11-year clinic , and the effect size was similar to the seven-year clinic (β = 0.33). Neither of the SNPs that associated strongly with measles showed good evidence for association at other timepoints, with the effect appearing to attenuate with age beyond seven-years.Lastly, replication of rs1634083 associated with antibodies against measles virus was shown at the 11-year clinic , an intronic variant located in genes SUGCT and LOC105375245. However, the effect size was in the opposite direction.Furthermore, we attempted to replicate the associations identified in the ALSPAC seven-year clinic in an independent cohort, UK Biobank , and findings are shown in P < 5×10-8) with Epstein-Barr virus (10 associations), herpes simplex virus 1 (one association) and T. gondii (one association) in UK Biobank (P < 0.001): rs9264759, rs1043620, rs2523502, rs3117139 and rs3096695, with effects in the same direction compared to UK Biobank, with the exception of rs1043620 in which the effect was in the opposite direction (P > 0.485). In addition, three EBV antibody associations were not able to be replicated as no suitable LD proxy SNP was identified (R2 < 0.6) in ALSPAC, and similarly none of the associations with antibodies against herpes simplex virus 1 or T. gondii were able to be replicated.We also conducted the analysis in the opposite direction, with a GWAS in UK Biobank as a discovery cohort and ALSPAC seven-year clinic as replication. Five antibodies in UK Biobank overlapped with ALSPAC  . We found very high concordance between posterior probabilities of imputed genotypes between the two methods at two- and four-digit resolutions (P < 6.2 × 10-4) and at a 4-digit resolution (P < 5.0 × 10-4) are shown in We performed HLA association analyses for 14 antibodies at two- and four-digit resolutions using both HLA imputation methods in ALSPAC. The associations that exceeded the HLA-wide corrected -value thresholds at a 2-digit resolution (P < 4.4×10-5) remained associated with antibodies against beta-casein protein, feline herpes virus and H. pylori. At a 4-digit resolution (P < 3.5×10-5), six HLA alleles remained associated with antibodies against beta-casein protein, Epstein-Barr virus, feline herpes virus, and H. pylori.When further correcting for the 14 antibodies tested, seven HLA alleles at a 2-digit resolution (H. pylori antibodies (other infections were not available). All eight Epstein Barr virus antibodies associations showed strong replication signals with the same direction of effect, with P <1×10-9. However, the four associations with H. pylori did not replicate , and 17 HLA associations were identified with five antibodies at a four-digit resolution (P < 2.8×10-5) in UK Biobank (P < 0.003) and five HLA alleles at a four-digit resolution (P < 0.003) associated with Epstein-Barr virus antibodies replicated in ALSPAC, with all effect estimates consistently showing the same direction of effects  with two antibodies, measles virus and T. gondii, at the ALSPAC seven-year clinical time point. Associations linking these loci with their respective antibodies have not been previously reported. Assessing the 26 associations that met a suggestive threshold (P < 1 × 10-6), the association between rs186721582 and Epstein-Barr virus antibodies replicated in UK Biobank. The associations between rs36020612 and T. gondii did not replicate (P > 5.9 × 10-4) and antibody data on the measles virus was not available. Stratifying individuals by MMR vaccine status for SNPs associated with antibodies against measles virus at the seven-year clinic showed stronger signal for individuals with an unknown status . For FHV antibodies, H. pylori and measles virus, the observed associations disappeared at the 15-year time point, which could be attributable to the reduction in sample size, lack of phenotypic variance, and possible false-positive associations identified at the seven-year time point.In genome-wide association analysis, we observed three genetic signals strongly associated (GRAMD1B with antibodies against T. gondii (P = 0.78), an antigen of T. gondii¸ with the effect size in the opposite direction. This lack of association could be due to the difference in statistical power contributing to the sample size of SAG1 protein domain (N = 1228) compared to T. gondii (N = 5010).Of particular interest in the main ALSPAC GWAS, was the association between rs36020612 located on . gondii –40, lymp. gondii , mean co. gondii , 43, ery. gondii , 44, blo. gondii , and imm. gondii , 46. HowMHC) class II region in ALSPAC and identified 20 associations of interest with antibodies against beta-casein protein, Epstein-Barr virus, feline herpes virus, H. pylori, and S. cerevisiae  which could possibly be a result of false-positive associations in ALSPAC at the seven-year clinic, and lack of phenotypic variance. To date, no studies have investigated the association of these HLA alleles and H. pylori in individuals of European ancestry. Studies using other ancestral populations have shown that HLA-DQB1*05:01 strongly increased the risk of gastric cancer in individuals of Mexican descent  associated with antibodies against measles virus, however we were unable to test for replication in UK Biobank due to data unavailability. Furthermore, we observed strong evidence of replication of the suggestive SNP (rs186721582) associated with Epstein-Barr virus antibodies in UK Biobank, suggesting the genetic effect is stronger in adults. Our study provides a useful resource for future studies looking to use ALSPAC antibody measurements as well as HLA alleles. It indicates that for future use of the measured antibodies in ALSPAC the most appropriate approach is to use the antibody level measures as a continuous variable. This study has highlighted the potential for identification of host genetic risk factors for several common infections, and demonstrates that if similar data is collected in other cohorts, future meta-analysis GWAS is likely to be a fruitful endeavour in uncovering the genetic and biological mechanisms of infection susceptibility.In summary, our study has confirmed known HLA allele associations with Epstein-Barr virus in a younger age group (seven-years) and replicated results in the adult population, UK Biobank. In addition, in the discovery phase we have identified four potentially novel genetic associations, with rs36020612 showing strong evidence of association with http://www.bristol.ac.uk/alspac/researchers/our-data/). Access to ALSPAC research data must be requested using the formal procedures and is subject to eligibility, the ALSPAC funder’s terms and conditions and University of Bristol policies and procedures. Requests to access these datasets should be directed to alspac-exec@bristol.ac.uk.The ALSPAC study website contains details of all the data that is available through a fully searchable data dictionary and variable search tool . This research was specifically funded by Wellcome Trust and MRC, 076467/Z/05/Z. AC is funded by the Jonathan and Georgina de Pass studentship. This work was supported by the Integrative Epidemiology Unit, which receives funding from the UK Medical Research Council and the University of Bristol .The UK Medical Research Council and Wellcome (Grant ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website (The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Both PCs and TCs showed similar acute-phase glycoprotein profiles, even when TCs lost the virological control , and the serum acute-phase glycoprotein signature in PCs did not differ from that in HIV-negative subjects . Differences in serum glycoproteins A and B were significant only in ECs compared to HIV-typical progressors (TPs) with < 100 CD4+ T-cells (p < 0.001). 1H-NMR acute-phase glycoprotein profile does not distinguish TCs form PCs before the loss of viral control. ECs maintain a low-grade inflammatory state compared to TPs. PCs revealed a closer serum signature to HIV-negative subjects, reaffirming this phenotype as a closer model of functional control of HIV.Elite controllers (ECs) are an exceptional group of people living with HIV (PLWH) who maintain undetectable viral loads (VLs) despite not being on antiretroviral therapy (ART). However, this phenotype is heterogeneous, with some of these subjects losing virological control over time. In this longitudinal retrospective study, serum acute-phase glycoprotein profile assessed by proton nuclear magnetic resonance ( Elite controllers (ECs) are a select group of people living with HIV (PLWH) who maintain a circulating viral load (VL) at undetectable levels without antiretroviral treatment (ART) , 2. ThisAlthough it was once thought that ECs could have a favorable short- and long-term prognosis, recent real-life data have revealed that ECs are at increased risk of several non-AIDS events . Notably1H-NMR serum glycoprotein measurement encompasses the systemic inflammatory process more comprehensively than other individual biomarkers   were incTwenty-two elite controllers (ECs) were selected, defined as subjects who in the absence of prior or current ART since HIV diagnosis and during the 36 months of the follow-up maintained an undetectable VL. Two groups were distinguished: 11 ECs who lost spontaneous viral load control, defined by detection at least two consecutive measurements above 50 HIV-RNA copies/mL within a year (TCs); and 11 ECs who maintained virological control throughout the follow-up (PCs), as previously described .Regarding the glycoprotein profile, repeated analyses were performed during the follow-up in TCs: two years before the loss of virological control, one year before the loss of virological control (T-1), 6 months before the virological control, at the moment when viral load was detected (T0) and subsequently at one year after the spontaneous loss of control (T+1). In PCs, repeated analyses were also performed at least at two different time points, but no differences were found in the glycoprotein profiles during any of the follow-ups. Thus, median values were calculated and identified as T0 for the PC group Figure 1+ T-cells at starting ART) and HIV-typical progressors with non-severe immunosuppression (> 350 CD4+ T-cells at starting ART) , matched by sex and age with ECs . For theing ART) Figure 1ing ART) . Serum gAll the selected patients had be age over 18 years and no had concomitant acute or chronic conditions or was taking drugs  that could eventually modify the inflammatory status when the blood samples were collected.1H-NMR for glycoprotein profiling as previously reported , and graphical representations were generated with GraphPad Prism software .The continuous variables presented a non-normal distribution due to the small sample size. Data are expressed as medians and 25th and 75th percentiles. Categorical variables are expressed as percentages. Differences between two groups were analysed using the nonparametric Mann-Whitney test, and for multiple comparisons one- way ANOVA followed by Bonferroni’s The study and all of the research protocols were conducted in accordance with the recommendations of the Ethical and Scientific Committees, and all of them were approved by the Committee for Ethical Clinical Research by following the rules of Good Clinical Practice from the Institut d’Investigació Sanitària Pere Virgili (CEIM 041/2019). The CEIm IISPV is an independent committee, consisting of health and non-health professionals that supervise the correct compliance to the ethical principles governing clinical trials and research projects that are performed in our region, specifically in terms of methodology, ethics and laws. An informed consent form signed by each participant was obtained in accordance with the Declaration of Helsinki and which includes the allowance to use the samples stored in the Biobank for related biomedical research projects.+ T-cell or CD8+T-cell counts between TCs and PCs. The T0 since HIV diagnosis was not statistically significance between TCs than PCs (P=0.061).A flow chart illustrating patient enrolment and categorization is shown in To predict the loss of control in TCs, serum glycoprotein concentration and H/W ratios analyzed at 24 months, 12 months and 6 months before the loss of control in TCs were compared to T0 values in the PC group. No differences were observed among the groups of studies and thus, we selected data from 12 months before the loss of control (T-1) as the representative value for TCs Table 2.vs. 402.4, respectively, P = 0.044; GlycA, 691.4 vs. 757.5, respectively, P= 0.054; H/W Glyc B, 4.5 vs. 5.1, respectively, P = 0.049; H/W Glyc A, 15.7 vs. 18.7, respectively, P = 0.002). However, when the serum glycoprotein signature in healthy HIV-negative subjects was separately compared to each group of PLWH-EC, only the difference in TCs remained significant compared to the group of healthy HIV-negative subjects , matched by sex and age . PLWH-TP showed higher serum glycoprotein concentrations and H/W ratios than the PLWH-EC group , serum Glyc A and Glyc B concentration and H/W Glyc A and Glyc B ratios resulted significantly higher in TP with < 100 CD4+ T-cells compared to both, PC and TCs , was also evaluated in a longitudinal analysis. VL evolution from TC after one year of loss of control was not significantly different from baseline (T0)  or the decrease in the CD4+ T-cell counts . However, TC showed a slightly decreased acute-phase glycoprotein profile at one year compared to T0, although the results were only significant for serum GlycA concentrations (P = 0.05). In fact, after one year of viral rebound (T+1), the serum glycoprotein profile in TCs (716.7 [671.4-835.5] µmol/L) became more similar to the serum glycoprotein profile of PCs at T0 (746.2 [638.7-887.8] µmol/L), although maintained a sustained low-grade inflammation in PLWH-EC compared to HIV-negative individuals (691.4 [664.8 – 755.5] µmol/L) Figure 3The loss of spontaneous viral control in TC has been extensively investigated. According to different publications, it seems that there is no single mechanism responsible for controlling viral replication. This situation could be associated with genetic factors in the host  , low pol1H-NMR in PLWH-EC. Low-grade inflammation seems to remain present in PLWH-EC and is one of the reasons why the use of antiretrovirals is debated despite spontaneous suppression of the virus. In our previous work, glycoproteins were prognostic of immune recovery in PLWH . In short, as seen in previous publications, a higher level of glycoproteins will be associated with decreased CD4 counts and higher viral load. This outcome is also reflected when separating the TPs into subgroups, in which the subgroup with the best immune status (CD4+ T-cell> 350) presented a glycoprotein profile more similar to the PLWH-EC compared to the group of PLWH-TP with severe immune damage (CD4+ T-cell <100 cells/µL).In the present study, we observed that the glycoprotein profile remained the same between PC and TC individuals prior to the spontaneous loss of viral control. However, a significant association of H/W GlycA was observed with viral load in TCs once they lost viral control (T0). This finding is in line with previous publications  in whichThe main limitation of the study is the small number of subjects in each arm of the study design which probably means there was insufficient power to detect significant predictive value of the GlycA and B measures, since in previous studies they did predict immune recovery . However1H-NMR have been associated, within the same disease, with worse states . The patients/participants provided their written informed consent to participate in this study.All authors contributed to the article and approved the submitted version. The authors contributions are as follows: experimental design  and intellectual guidance . recruitment of subjects (JP and ER-M) and sample procurement (AIM and JM). Data collection (AIM and NA). data analysis and interpretation . manuscript preparation (AIM and JM). AI-M, JM, AC, FV, LM, and AR were responsible for the study design, data analysis, and article development. FV, LM and AR reviewed and edited the manuscript.This research was funded by the Fondo de Investigacion Sanitaria -ISCIII-FEDER ; Programa de Suport als Grups de Recerca AGAUR (2017SGR948); the SPANISH AIDS Research Network -ISCIII-FEDER (Spain) and Centro de Investigación Biomédica en Red de Enfermedades Infecciosas-ISCIII , Madrid, Spain. JM is supported by the Universitat Rovira i Virgili under grant agreement “2019PMF-PIPF-18,” through the call “Martí Franquès Research Fellowship Programme”. FV is supported by grants from the Programa de Intensificación de Investigadores (INT20/00031)-ISCIII. AR is supported by a grant from IISPV through the project “2019/IISPV/05” , by GeSIDA through the “III Premio para Jóvenes Investigadores 2019” and by the Instituto de Salud Carlos III (ISCIII) under grant agreement “CP19/00146” through the Miguel Servet Program.NA is stockowner of Biosfer Teslab, the company that commercializes the glycoprotein profiling described in the present manuscript.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Conversion from conventional ventilation to INTELLiVENT-ASV resulted in a lower intensity of ventilation. These findings may favor the use of INTELLiVENT-ASV in COVID-19 ARDS patients, but future studies remain needed to see if the reduction in the intensity of ventilation translates into clinical benefits.Driving pressure (ΔP) and mechanical power (MP) are associated with outcomes in critically ill patients, irrespective of the presence of Acute Respiratory Distress Syndrome (ARDS). INTELLiVENT-ASV, a fully automated ventilatory mode, controls the settings that affect ΔP and MP. This study compared the intensity of ventilation (ΔP and MP) with INTELLiVENT-ASV versus conventional ventilation in a cohort of COVID-19 ARDS patients in two intensive care units in the Netherlands. The coprimary endpoints were ΔP and MP before and after converting from conventional ventilation to INTELLiVENT-ASV. Compared to conventional ventilation, INTELLiVENT-ASV delivered ventilation with a lower ΔP and less MP. With conventional ventilation, ΔP was 13 cmH T) and, as such, represents the strain applied to the lung with each breath during mechanical ventilation [T and ΔP, but also respiratory rate (RR) [Limiting the intensity of ventilation could improve outcomes in patients with acute respiratory distress syndrome (ARDS) ,2,3. Thitilation . The sectilation ,7. The late (RR) ,9.It can be very challenging, if not practically impossible, to keep the intensity of ventilation low at all times. INTELLiVENT-Adaptive Support Ventilation (ASV) is a fully automated, closed-loop ventilatory mode that automatically controls gas exchange at the lowest work of breathing  and at tIt is uncertain whether INTELLiVENT-ASV affects the intensity of ventilation in COVID-19 patients with ARDS. The aim of this substudy of the ‘PRactice of VENTilation in COVID-19’ (PRoVENT–COVID) study  was to cwww.clinicaltrials.gov (accessed on 15 April 2020); trial identification number NCT04346342). The need for informed consent was waived because of the observational nature of this study and because the decision to use conventional ventilation, or INTELLiVENT-ASV, was left to the discretion of attending physicians and nurses and in accordance with the local guideline for ventilation in the 2 ICUs. Before and after the conversion to INTELLiVENT-ASV, fairly identical target ranges for end-tidal carbon dioxide (etCO2) and peripheral oxygen saturation (SpO2) were used. We targeted normocapnia and normoxemia with both ventilation modes in all patients. Pressure limits were left unchanged. Additional details on ventilator settings are depicted in This was a retrospective 2-center substudy within a large national observational study undertaken during the first wave of the COVID-19 pandemic in the Netherlands. The substudy was conducted at the Intensive Care Unit (ICU) of the Reinier de Graaf Hoss alignmentpital in Delft and the ICU of the Amsterdam University Medical Centers, ‘location AMC’ in Amsterdam, the Netherlands. The study protocol (number W20_157#20.171) was approved on 7 April 2020 by the Institutional Review Board of the AMC (chairperson Prof. Dr. J.A. Swinkels), Amsterdam, and was prepublished , and thePatients aged 18 years or older with COVID-19 confirmed with RT-PCR for SARS-CoV-2 and ARDS according to the Berlin definition  were eliThe severity of illness, medication and vital signs were obtained at baseline. Ventilation variables and parameters were collected at 4 consecutive timepoints: at 2 and 1 h before and at 1 and 2 h after conversion from conventional ventilation to INTELLiVENT-ASV. Thus, we had a maximum of 4 timepoints at which ΔP and MP could be calculated. ΔP was calculated as plateau pressure (Pplat) minus positive end-expiratory pressure (PEEP). MP was calculated as :MP  or mean (±SD) for continuous variables. Proportions were compared using the chi-squared test or Fisher exact test as required by variable distribution, and continuous variables were compared using the Wilcoxon Rank Sum Test or the Wilcoxon signed-rank test as appropriate. Effects are presented with a 95% confidence interval (95% CI).A mixed-effects generalized linear model with a Gaussian distribution was used, wherein ventilation mode was used as a fixed effect and patients as a random effect, to account for repeated measurements.T, PEEP, Pmax, RR and other ventilator parameters with INTELLiVENT-ASV versus conventional ventilation, cumulative distribution plots were constructed. Medians were compared using the Wilcoxon signed-rank test. In addition, the relation between VT and ΔP at the 4 timepoints was visualized in plots using least square method regression analysis. Scatterplots and line graphs were also used to show how individual changes in VT related to changes in ΔP.To compare ΔP, MP, VWe performed 2 post hoc analyses. In the first post hoc analysis, MP was calculated using another equation than the one proposed above as :MP (J/miRS) and was calculated as:In the second post hoc analysis, MP was normalized for respiratory system compliance  and R version 3.6.3 .There were no missing data. A Between 1 March and 1 June 2020, 144 patients were screened for eligibility . A totalDemographic data, including preceding medication, the severity of disease and comorbidities, are presented in 2O, the median MP was 21.5 (IQR 14.6 to 32.1) and 24.8 (IQR 19.4 to 31) J/min. 1 and 2 h after the conversion, the median ΔP was 11 (IQR 9 to 14) and 10 (IQR 8 to 14) cmH2O (mean difference –2 cmH2O (95% CI –2.5 to –1.2 cm H2O); p < 0.001) and the median MP was 18.8 (IQR 12.2 to 22) and 17.5 (IQR 12.2 to 21.1) J/min (mean difference of –7.7 J/min (95% CI –8.8 to –5.8 J/min); p < 0.001)  and 13 (IQR 10 to 17) cmH< 0.001) .T, but most patients maintained a VT of < 8 mL/kg PBW. Before conversion to INTELLiVENT-ASV, 7 of 51 patients (14%) received ventilation with a VT > 8 mL/kg PBW. At 1 and 2 h after conversion, 10 (19%) and 8 patients (16%) received ventilation with a VT of > 8 mL/kg PBW. With INTELLiVENT-ASV, when VT increased, ΔP decreased. In addition, when ΔP was high with conventional ventilation, VT decreased with INTELLiVENT-ASV  a reduction in ΔP and 2) a reduction in MP. Limiting ΔP and MP have been proposed as targets that may result in better outcomes in patients with ARDS  a reduct, and autThis study has strengths and limitations. First, this study was performed in ICUs with physicians and nurses with extensive experience in the use of lung-protective ventilation and also the use of INTELLiVENT-ASV. The first can be seen as a strength, as this means that we compared ‘best practice’ in lung-protective ventilation during conventional ventilation with fully automated ventilation. However, the second could be seen as a limitation, as this may reduce the generalizability of the findings. Of note, adequate input into the ventilator by the caregivers remains necessary for the optimal use of INTELLiVENT-ASV, and the quality of input increases with experience. Other strengths are that we strictly followed a predefined analysis plan, and we had no missing data. One limitation is that we did not use a cross-over, cross-back approach, which means that part of the findings may be explained by natural changes in respiratory physiology. For example, the changes in ΔP and MP over the hours we observed in the patients could also have been caused by an improvement in the clinical condition, independent of the way ventilation was applied. This, however, is very unlikely considering the fact that the overarching study findings showed only marginal changes in ventilator settings and parameters of interest over the first 4 days of invasive ventilation . Last, wOur findings are in line with those from previous investigations testing the safety, feasibility and effectiveness of INTELLiVENT-ASV in different patient groups. In one randomized clinical trial in postcardiac surgery patients , INTELLiThe findings did not change in the sensitivity analysis using an alternate equation for calculating MP. The original equation is designed for use in volume-controlled ventilation, while we used pressure-controlled ventilation before changing the ventilator mode to INTELLiVENT-ASV, and INTELLiVENT-ASV itself is a mode that is based on the principles of pressure-controlled ventilation. Findings also did not change in a sensitivity analysis in which MP was normalized. The rationale behind normalization is that ventilator-induced lung injury derives from the interaction between the causal factors of two broad categories—the machine output and the condition of a healthy or diseased lung. This means that for the same amount of MP, the lung volume determines the intensity.2 and SpO2 values were not affected. We hypothesize that the slight increase in VT resulted in the recruitment of parts of the lung sufficient to compensate for the lower minute volume.One key ventilator setting that showed a remarkable change from before to after the conversion to automated ventilation was the RR. Previous studies have shown an association of higher RR with poor outcomes . The decT. However, in most patients, VT remained largely within the widely agreed safety zone, i.e., <8 mL/kg PBW. The increased median CRS with INTELLiVENT-ASV could mean that the larger VT was applied to a better-aerated lung. The lower ΔP and lower upper airway pressure with INTELLiVENT-ASV are in line with this suggestion. With INTELLiVENT-ASV, median ΔP remained below the suggested safety limit of 15 cm H2O and was lower than with conventional ventilation in most patients. One interesting finding of our study was that when ΔP was high with conventional ventilation, VT decreased with INTELLiVENT-ASV, suggesting less overinflation after the conversion. While we acknowledge the importance of using a low VT in patients with ARDS, a small increase in VT accompanied by decreases in ΔP and MP may be acceptable.Compared to conventional ventilation, INTELLiVENT-ASV resulted in a somewhat higher median VT, as VT remained within the generally accepted safety limits. The effect of INTELLiVENT-ASV on MP seems mainly driven by a reduction in the respiratory rate.Conversion from conventional ventilation to INTELLiVENT-ASV resulted in a lower intensity of ventilation in this cohort of COVID-19 ARDS patients. The conversion resulted in a small but acceptable increase in V